MLOps Engineer

Responsibilities

• Own the complete lifecycle transition from AI/ML experimentation to reliable, high-performance production deployment
• Build, maintain, and scale infrastructure, automation, and CI/CD workflows for efficient model deployment
• Implement production monitoring systems, visibility dashboards, and data/concept drift detection
• Manage experiment tracking and model versioning to ensure full reproducibility and traceability
• Partner with data scientists and AI researchers to translate experimental models into production-ready solutions
• Manage cloud environments and GPU compute resources to ensure scalable and cost-effective operations

Requirements

• Professional experience in MLOps, DevOps, Data Engineering, Machine Learning, or Software Engineering
• Degree in Computer Science, Software Engineering, or a related technical discipline
• Must reside in Dallas, TX, and be willing to work onsite
• Hands-on experience with experiment tracking, model registry/versioning, drift detection, and production monitoring
• Practical experience navigating cloud environments and managing/provisioning GPU compute resources
• Deep understanding of containerization (Docker, Kubernetes) and designing robust CI/CD pipelines
• Solid conceptual understanding of AI/ML fundamentals
• Upper-intermediate English level

Benefits

• Professional growth through mentorship, TechTalks, and personalized growth roadmaps
• Competitive USD-based compensation
• Budgets for education, fitness, and team activities
• Opportunity to work on exciting projects with top-tier clients and Fortune 500 enterprises
• Flexible scheduling options to support work-life balance

About the Company

AgileEngine is a high-growth technology services company that helps clients build scalable software solutions. We connect top-tier engineering talent with leading product brands and enterprises globally.